Many processes have nonlinearities and/or extreme variation between batches (or tests or experiments or subjects or otherwise), and this makes the automation of these processes very difficult. In biological systems, inter-subject (human, non-human animal, tissue or other) variation is large. Parameters describing response to inputs (electrical, chemical or otherwise) vary greatly within the same species, with variation of as much as 50% being common.
The current description, while applicable to any process control system displaying nonlinear behavior and variation, was developed through work done in automated drug delivery in general and automated delivery of neuromuscular blocking (NMB) drugs in specific. Thus, the examples and instantiations presented will concentrate on automated drug delivery. The following discussion provides a general description of certain aspects of the background and while instructive does not provide specific factual representations.
Automated drug delivery (or drug administration under computer guidance or control) can improve drug therapy by allowing for more efficient and smoother delivery. Automated drug delivery may reduce drug usage, side effects and costs; permit health care staff to work more efficiently; and allow the safe use of drugs that are difficult to administer manually, leading to better care for the patient. Computer controlled administration of insulin, blood pressure medications, neuromuscular blocking (NMB) agents and other drugs has been attempted previously with limited success. Application of computer control to NMB drugs is a rich field, and a subject that is both fraught with nonlinearities in response and with great inter- and intra-patient variability. Computer control of NMB drugs will be discussed here to illuminate the difficulties in controlling these nonlinear and variance-prone systems.
NMB drugs produce paralysis to prevent motion, permit tracheal intubation and allow access to deep structures with smaller incisions. As NMB drugs have high therapeutic indices in hospital settings, they are often used in excess of minimal effective requirements. A strategy for administration is to provide an overdose to prolong paralysis, monitor for returning muscle function and, once it returns, overdose again [1]. The large dose delivers rapid onset of paralysis, quicker surgical conditions, and avoids titration to a precise anesthetic setpoint and regulation once there [2].
The practice of serial bolus administration of NMB drugs leads to instances of under- and overdosing. Overdosing is important at the end of the case when the patient should be extubated and awakened, but cannot be due to the presence of too much NMB drug. Overdosing creates delays while the NMB drug wears out and due to improper neuromuscular monitoring, results in a great many patients being extubated prematurely. Incidence of post-operative residual curarization (PORC) is between five and 10% of patients for intermediate-acting compounds, such as rocuronium (Eriksson [3]), and between sixteen and 42% of patients will have To4 measurements of less than 0.7 to 0.8 (Murphy [4]), which can lead to impaired hypoxic ventilatory response and other complications. The overdosing strategy is also a source of inconvenience should complications arise and the surgical conditions change, which is not uncommon. After paralysis and induction have taken place, examination of the patient may reveal a complication such as extensive invasive carcinoma, which may require different staff, equipment and procedures. Changes in staff, equipment and procedures will lead to cancellation of the scheduled procedure, and the anesthesiologist and attending nurses will have to wait until the NMB wears off enough to allow reversal.
As another example, in Harrington rod insertion for reshaping the spine, the surgeon assesses whether or not the rods have impinged nerves by the ability of the patient to respond physically. Testing can be performed only after the return of muscle function. Automatic control could keep the patient less paralyzed until a test is required, reduce drug administration to allow function to return, and then re-paralyze for continued work with less waiting time by the surgical staff.
It is important to avoid underdosing during the case at it can be a source of intra-operative adverse events. Patients with ineffective levels of NMB will cough and buck on the ventilator, possibly resulting in extrusion of internal organs, and will move, possibly resulting in injury from other means. As well, muscles will be tighter and will resist surgical interventions making the surgeons' job more difficult.
The problems associated with serial bolus dosing are intensified due to the current practice in monitoring of NMB being deficient. In an ideal scenario, the patient would be monitored continuously throughout the procedure so that the anesthesiologist and medical staff would be constantly aware of the state of the patient's muscle function and would be able to provide appropriate amounts of NMB drugs to maintain the patient at an ideal level of muscle function throughout the procedure. However, continuous NMB monitoring by the anesthesiologist is labor intensive for someone who—for the betterment of the patient's health—typically cannot devote themselves solely to the NMT sensor. This is one reason why objective monitoring is not done continuously, but instead either only at key points in the case such as extubation, or not at all. Computer control of NMB could reduce anesthesiologists' monitoring of muscle response, reduce loss of reversibility at procedure's end due to over-paralysis, and give anesthesiologists fine control of muscle tone. Representative control efforts include bang-bang [5], Proportional Integral Derivative (PID) control [6], PID/Smith predictor [7] and fuzzy logic control [8]. Some of the controllers developed have not been stable or robust enough to handle the intra- and inter-patient variability present.
Other controllers have achieved near constant levels of blockade in relatively controlled experimental settings, but are associated with significant constraints that thus far have impeded their utility in routine clinical practice. For example, most involve the use of single twitch stimulation to measure response (ST or T1%). In addition to the often considerable associated setup time, the use of single twitch stimulation necessitates a stable control [9] and T1% baseline stabilization requires up to 20 minutes between induction and NMB drug administration [10], unnecessarily exposing patients to the risks of an unprotected airway and creating unacceptable operating room time delays. Furthermore, the typical controller setpoint is T1%=10% (i.e., 90% single twitch suppression) [8, 10, 11, 12] which represents a potentially non-reversible state.
Adaptive control may help accommodate the patient variance. An adaptive controller usually comprises a fixed-structure controller with adjustable parameters and a mechanism for automatically adjusting those parameters. Adaptive control's roots begin in the 1950s with the development of the autopilot for high-performance aircraft [13]. Since then there has been much theoretical development and application. An in-depth review of this field appears in [13]. An example of an adaptive control technique that has been used not just in chemical batch processes but in clinical application as well is Generalized Predictive Control [14, 15], a general-purpose adaptive control method. This method was used in the operating room in control of NMB as described in [16].
Patent Documents
See U.S. Pat. Nos. 2,690,178, 4,080,966, 4,280,494, 4,291,705 4,370,983, 4,392,849, 4,533,346, 4,741,732, 5,256,156, 5,335,164, 5,409,456, 5,520,637, 5,713,856, 5,822,715, 5,957,860, 6,042,579, 6,186,977, 6,328,708, 6,379,301, 6,389,312, 6,511,453, 6,599,281, 6,605,072, 6,725,086, 6,796,956, 6,807,965, 6,830,047 and 7,220,240; WIPO 93/14807 and 00/67820; and US applications 2006/0217628, 2003/0156143 and 2007/0255135.